SerenialTech builds AI agents that do real work inside the software your business already uses. An agent is more than a chatbot: it can read your data, call your tools — a store, CRM, ERP, ad account or helpdesk — and finish a task, asking a person to approve anything that spends money or changes what customers see.
Our flagship system, Hermes, is a team of AI agents that runs marketing for a Shopify brand. The owner asks for things in plain English on Discord; an orchestrator agent hands the work to specialists that write copy, audit the store, plan social posts and prepare Meta Ads and Google Ads campaigns. Nothing is published or spent without approval.
We also add AI to existing products: assistants that answer from your documentation, smart search over tickets and files, summaries for busy teams and document processing that turns PDFs and spreadsheets into structured data.
Who we work with
Our AI clients include direct-to-consumer brands that want marketing help without a larger team, manufacturers and distributors who want quicker quotes and order answers, service companies drowning in tickets and documents, and software companies adding assistant features to their own products. Most are not AI specialists; they know which tasks consume too much time and want a dependable system that handles them safely, with a clear view of what it costs to run each month.
Why choose SerenialTech for AI Agent Development
Production systems, not demos
Hermes runs real marketing work for a real store every week. Building it taught us what matters once the demo is over: retries when an API fails, rate limits, cost tracking, logs you can audit and a way for a person to stop everything with one command. Every agent we deliver inherits those lessons.
Honest about what AI can and cannot do
Some tasks suit AI well; others are better solved with ordinary software or a clearer process. We tell you which is which before you invest. When an agent is the right answer, we design it to cite its sources, admit uncertainty and hand difficult cases back to a person.
Integrated with your software
An agent is only as useful as the tools it can reach. Our team also builds ERP systems, online stores, websites and mobile apps, so we can connect an agent to your systems properly — or add the missing API it needs — rather than leaving it to copy and paste between windows.
Planning your AI Agent Development project
Pick a task with a clear finish line
Good first agent projects have a measurable outcome: a draft ready for review, a ticket categorised, a quote prepared. Avoid vague goals such as “help the team with marketing”. A narrow first task builds trust, shows the real cost per run and gives you data for the next, more ambitious step.
Prepare access and data
Agents need well-defined access to the systems they use. List which accounts and APIs are involved, who owns them, what the agent may read and what it may change. Clean, current data matters more than the choice of model; an agent answering from outdated price lists will confidently give outdated answers.
Decide where people stay in control
For each action, decide whether the agent may act alone, must ask for approval or must never act. Publishing content, spending money and changing prices usually need approval at first. Review the audit log regularly during the first weeks, then widen autonomy only where the agent has proved reliable.